investigating the motivation for understanding enterprise … · 2017-04-12 · sprinthall et al....
Post on 26-Mar-2020
8 Views
Preview:
TRANSCRIPT
1
Investigating the Motivation for Enterprise Education: A CaRBS based Exposition
Purpose
This study investigates student motivations for undertaking an EU funded entrepreneurship
education programme in the Objective One areas of Wales and the relationships between
motivation characteristics and their ultimate employment and self-employment aspirations.
For both statistical and explanatory reasons a novel data mining technique (CaRBS) is used to
undertake the equivalent of classification analysis. The study considers what relationships
certain motivation characteristics have to students' aspirations, specifically in terms of their
intention to be self-employed or employed.
Design/methodology/approach The study examined enrolment data of 720 students on an entrepreneurial education
programme called E-College Wales, and have known aspirations to either employment or
self-employment. The Classification and Ranking Belief Simplex (CaRBS) technique is
employed in the classification analyses undertaken, which offers an uncertain reasoning
based visual approach to the exposition of findings, and which has particular relevance when
the data is non-parametric and the considered potential relationships are non-linear.
Findings
The classification findings demonstrate the level of “contribution” of the different motivation
characteristics to the discernment of students between self-employed and employed
aspirations. The most strongly contributing characteristics were, motivations to undertake a
business start-up, interest in the subject matter and intent to achieve the qualification. For
these characteristics, further understanding is provided with respect to the student
demographics of gender and student age (in terms of the association with aspirations towards
being self-employed or employed). For example, with respect to start-up, the older the
student, the increasing association with employment rather than self-employment career
aspirations.
Research limitations/implications
The study identifies candidate motivation characteristics and the demographic profile for
student's undertaking an entrepreneurial education programme. Knowing applicant
aspirations should inform course design, pedagogy and its inherent flexibility, and recognise
the specific needs of certain student types.
Originality/value
The study contributes to the literature examining the motivations for undertaking
entrepreneurship education and categorising motivating factors. These findings will be of
value to both education providers and researchers.
Key words: Aspirations, CaRBS, Entrepreneurship Education, Employment, Motivations,
Self-employment.
Article Classification: Research paper
2
Introduction: Entrepreneurial Education
The small and medium enterprise (SME) sector plays a key role in contributing to
innovation and wealth creation, employment and economic growth in all industrialised and
developing countries (Robson and Bennett, 2000). Within the UK context, specifically, the
SME community accounts for 52.4% of employment (Pickernell et al., 2011). Thus, reality
suggests most current Higher Education (HE) students are likely to be employed within the
SME sector at some time, and therefore, must be equipped with the appropriate knowledge
and skills to prosper (Anderson and Jack, 2008).
Harrison and Leitch (2010) also suggest that researchers, governments and policy
makers, are increasingly recognising the significant role that HE in particular, must play in
economic development. Consequently, over the past decade there has been a significant
global increase in entrepreneurship programmes aimed at augmenting entrepreneurial activity
at all levels (Fayolle et al., 2006; Hamidi et al., 2008).
This increased demand has been fuelled by four key drivers of change, namely, global,
societal, organisation and individual levels (Henry et al., 2005). Globally, the reduction in,
trade barriers, information technology and telecommunications progression and enhancement
of transportation infrastructure, have offered new opportunities and increased business
uncertainty and complexity (Jones et al., 2013). At a societal level, factors such as
privatisation, deregulation, increasing environmental impacts and catering for the rights of
minority groups of the individual, have compounded business process complexity. At an
organisational level, decentralisation, downsizing, business process re-engineering, increased
strategic alliances and mergers and workplace flexibility, have impacted to increase business
uncertainty. The outcome of such change is that the individual is faced with an increased
variety of employment opportunities and having to undertake a diversity of job roles during
their employment career including self-employment opportunities (Henry et al., 2005).
3
This suggests that entrepreneurship education, to the extent it may be useful, needs to
account for the lifelong learning aspects of potential entrepreneurship students. Much of the
debate on interventionism has centred on developing an environment in which
entrepreneurship can be encouraged and sustained (Gilbert et al., 2004). Jack and Anderson
(1999) and Matlay (2006) noted entrepreneurship education has climbed the political agenda,
within industrialised and developing economies, as a means of encouraging both business
growth and employment within a challenging economic environment.
Within this discussion, the role of education and training has taken prominence
(Pittaway and Cope, 2007). Previously, Watson et al. (1998) suggest motivation for business
start-up is a key factor towards successful entrepreneurship activity. This is based on the
premise whereby it is possible to provide individuals with the requisite skills and knowledge
required to start-up and develop a new venture (Gorman et al., 1997; Kuratko, 2005). Whilst
many individuals already possess distinct attributes and competencies which lend themselves
to an entrepreneurial career, recent studies suggest entrepreneurship can also be encouraged
through education and training (Hytti and O’Gorman, 2004; Harris and Gibson, 2008).
Zeithaml and Rice (1987), Hills (1988) and Solomon et al. (2002), in the USA and
Johannisson et al. (1998) within Europe, suggested the primary goal of such programmes was
to increase student awareness of entrepreneurship as a process, and thereafter, increase
awareness of the attainability of an entrepreneurial career. Clark et al. (1984) and Cho (1998)
claim entrepreneurship education could provide motivation for venture creation. Several
studies have associated successful completion of entrepreneurial education with individuals
undertaking business start-up activities (Kolvereid and Moen, 1997; Osborne et al., 2000;
Dumas, 2001; McLarty, 2005; Dickson et al., 2008). Studies by Robinson and Sexton (1994),
Basu and Goswami (1999), Delmar and Davidsson (2000), Brooksbank and Jones-Evans
4
(2005) and Wennekers et al. (2005), indicated prior educational attainment was positively
correlated to entrepreneurial activity.
This evidence has provided the impetus for a dramatic increase in the number of
entrepreneurship courses being offered by HE institutions globally (Katz, 2003; Fayolle,
2005). Von Graevenitz et al. (2010) however, notes that the research on the effects of
entrepreneurship education still has significant omissions, and further studies are required to
consider the understanding of entrepreneurial perceptions and intentions (McMullan et al.,
2008). Several recent studies have explored the short terms impact of entrepreneurial
education upon attitude and intent, for example Levie et al. (2009), Packham et al. (2010)
and Lange et al. (2011).
Many courses have been criticised, for example, as only providing a traditional,
corporatist approach to entrepreneurship education. This has been perceived as often having
failed to prepare nascent entrepreneurs for successful business start-up (Gibb, 1993; 1997;
2005; Henry et al., 2005). Much of the prior research, therefore, focuses on establishing an
association between education and entrepreneurship. These studies have been successful in
establishing a link between education attainment, entrepreneurial activity and advocating the
role education plays in promoting entrepreneurship as a viable career option (Rosa, 2003;
Kuratko, 2005; Souitaris et al., 2007). Creating and sustaining a new business start-up,
however, also requires sufficient motivation to surmount the hardships and frustrations
involved (Hisrich and Peters, 1998; Stewart et al., 1999; Kuratko and Hodgetts, 2001; Shane
et al., 2003). Hence, the motivation to engage in entrepreneurial activity is a profound issue
which can influence the business chances of success (Watson et al., 1998; Shane et al., 2003).
Research examining the underpinning motivations of students to enrol and complete
formal enterprise education, however, remains limited (Segal et al., 2005). As
entrepreneurship education courses are also not homogeneous in content, level, student
5
characteristics (e.g. age, gender balance, background etc.), or funding (e.g. student funded,
university funded or EU programme funded for example), this suggests a need to build a
research base utilising case study type approaches to identify underlying factors and
motivations which can also be used to develop future research.
This study, therefore, investigates these underlying factors or motivational
characteristics of a specific non-traditional (in terms of age) group of students for undertaking
a specific EU funded undergraduate entrepreneurial HE (full degree) programme, utilising a
novel non-parametric data mining technique (Classification and Ranking Belief Simplex -
CaRBS). Reasons for the utilisation of CaRBS are many-fold, including being linked both to
the non-parametric nature of the data, but also to the often non-linear nature of the
relationships (which lend themselves to a data mining approach from which more detailed
future study might follow), and the ability to more clearly explain the relationships through a
visual exposition of findings.
The overriding research aim considered here is what relationships certain motivational
characteristics have to the students’ ultimate entrepreneurship career aspirations, in terms of
their intention to be self-employed or employed. Moreover, how levels of influence of
student motivation characteristics (for example desire to undertake a business start-up post
programme) vary in the prescribed relationship when certain student demographics were also
considered. The paper will contribute to knowledge in providing greater understanding of
why students choose to undertake an entrepreneurship related degree and therefore positively
inform programme design and construction.
The structure of the paper is as follows: in section two, the salient literature on student
motivation for entrepreneurship is discussed, after which section three analyses students’
motivations for enterprise education. In section four, the methodology is presented. The
technical explanation of the CARBS technique is included within the appendices. The results
6
of the CaRBS-based analysis of the student motivation data set are thereafter presented,
including the influence of the considered motivation characteristics. Thereafter, further
exposition of the relevance of the motivation characteristics is undertaken, taking into
consideration certain demographics (gender and age) of the students. Finally, conclusions are
drawn and directions for future research proposed.
Literature: Student Motivation and Entrepreneurship
Sprinthall et al. (1994) and Hytti et al. (2010) suggest motivation drives an individual to act
in a certain manner. McClelland (1961) and Miner (1993) identified entrepreneurs have a
high need for achievement characterised by a desire to succeed and excel, which is more
attainable within an entrepreneurial career choice. Contrastingly, McClelland and Winter
(1969) found managers had a tendency to be higher in need for power and lower in need for
achievement. Watson et al. (1998) argued the motivation to start-up a small business was
influenced by characteristics such as work experience, personality, family environment and
societal norms. Jayawarna et al. (2013) summarised entrepreneurial motivations as economic
gain, desire for achievement, independence and control, personal development, improved
social status, opportunity to innovate and create new products, emulation of role models, and
contribution to community welfare (Birley and Westhead, 1994; Carter et al., 2003; Shane et
al., 2003; Cassar, 2007; Wu et al., 2007).
Porter and Lawler (1968) therefore proposed a model of entrepreneurial motivation
within which the four main factors which influenced the decision of an individual to start-up
a business were personal values, characteristics, situation and the status of the business
environment itself. Gilad and Levine (1986) proposed several ‘push’ and ‘pull’
characteristics which could be utilised to classify the motivations underpinning small
business start-up. Push characteristics related to negative forces such as: difficulties in
7
finding employment, job dissatisfaction, and inadequate remuneration. Conversely, pull
characteristics included independence; wealth and personal fulfilment were considered
positive motivational influences (Hisrich and Peters, 1998; Chell, 2001).
Importantly, there are both regional and national differences with respect to these
perceived motivations (Linan et al., 2011). In high-income countries, four times more adults
engaged in entrepreneurial activities through opportunity than necessity (Bosma and Harding,
2006). Moreover, Watson et al. (1998) concluded pull characteristics such as independence,
being one’s own boss, using creative skills, doing enjoyable work and wealth creation, were
more important than the push characteristics such as redundancy, frustration with employers
and need to earn a reasonable living. Segal et al. (2005) however, mooted that displaced
workers did not necessarily pursue an entrepreneurial option unless other influences were
evident. Roberts (1991), examining nascent entrepreneurship in the high technology sector,
found the majority of respondents did not consider personal wealth creation as a primary
motivator for self-employment. Entrepreneurial drivers including a need to achieve, a desire
for independence and dissatisfaction with current employment, were often cited as the
primary reasons associated with small business start-up.
In terms of HE as a source of entrepreneurs, Segal et al. (2005) determined that
motivations of undergraduate business students to embark on entrepreneurial careers were
related to an individual’s tolerance for risk, whilst Chell (2001) argued entrepreneurial
activity was underpinned by the need for achievement, independence and power. Galloway
and Brown (2002) found the rate of immediate start-ups by graduates was, however,
relatively low and suggested the lack of motivation was likely to be due to personal debt, lack
of collateral, limited industrial experience and alternative priorities. Segal et al. (2005)
argued graduates were less influenced by push characteristics due to limited employment
experience.
8
Student Motivations for undertaking Entrepreneurship Education
Young (1997) outlined several reasons as to why university students were motivated to study
entrepreneurship. These motivational characteristics included: independence, the acquisition
of skills and knowledge to enhance career progression and gaining an adjunct competitive
advantage in an independent professional career (e.g. dentist, accountant). Galloway and
Brown (2002) found that some students regarded such skills and knowledge as a buffer
against possible threats to an intended career path.
Therefore, it is important to explore the motivational characteristics which
underpinned students’ decision to undertake an entrepreneurial education programme and
their career aspirations thereafter. Entrepreneurial attitude is recognised as an accurate
predictor of planned behaviour and has been considered in several prior studies (Peterman
and Kennedy, 2003; Souitaris et al., 2007). Several studies have examined motivations for
undertaking an entrepreneurial career (Roberts, 1991; Galloway and Brown, 2002; Segal et
al., 2005; Taormina and Lao, 2007). Contrastingly, only a limited literature exists
considering the student motivations related to undertaking formal entrepreneurial education
(Young, 1997; Galloway and Brown, 2002). Even fewer, have looked at non-traditional
students and their motivations for studying entrepreneurial education.
The examination of the extent literature enables the identification of the following
potential motivational characteristics underpinning the decision to undertake formal
entrepreneurial education: -
i) Desire to undertake a business start-up (Start-Up)
ii) Desire to acquire management competencies (Management)
iii) Desire to achieve business growth (Business Growth)
iv) Desire to increase confidence in the option of an entrepreneurial career (Confidence)
v) Desire to develop interest in the subject matter (Interests)
9
vi) Desire to acquire entrepreneurial education related qualifications (Qualifications).
These characteristics, however, differ in terms of the degree to which they are likely
to be related to the desire for self-employment, as opposed to employment. For example,
Confidence, Start Up and Business Growth based motivational characteristics can be seen as
more likely to be related to self-employment aspirations than Management, Interests and
Qualifications. Each of these motivational characteristics is considered in turn, and
subsequently used in the CARBS analyses using the code identified:
Start-Up (StrtUp): Garavan and O'Cinneide (1994), Young (1997), Petridou et al.
(2009) and Peterson and Limbu (2010) suggested students undertake entrepreneurial related
programmes to provide the knowledge required for the business start-up process. Galloway
and Brown (2002) proposed students undertook entrepreneurial education to enhance their
prospects of undertaking an entrepreneurial start-up at some future point. Specifically, their
study noted 78% of students identified intent to start a business, of which 19% would enable
this process within five years, 38% between five and ten years and 43% after ten years.
Furthermore, it was apparent entrepreneurship education students were prepared to delay
their proposed business start-up for a significant time period, a trend noted previously in
Hayward and Sundes (1997).
Management (Mngmnt): Ineffective managerial competencies have long been
associated with small business failure (Walker et al., 2007). Anderson and Jack (2008)
identified individuals are attracted to the discipline of entrepreneurial education by the
opportunity of personal development and an adaptable skills base. Specifically, Cooper et al.
(2004) and Galloway et al. (2005) noted students seek education which provides them with
transferable skills including managerial competencies. Chrisman and McMullan (2004) and
Bhandari (2006) also noted that entrepreneurial education study enabled improved
managerial competency in areas such as sales and management of employees.
10
Business Growth (Grwth): The prior literature suggests entrepreneurship activity
enhances business growth (Acs and Audretsch, 2003; Audretsch and Keilbach, 2006; Praag
and Versloot, 2007). However, van Stel and Storey (2004) note entrepreneurial activity does
not necessarily stimulate business growth for several reasons (see also Hessels et al., 2008),
although Edelman et al. (2010) suggests that firm growth is widely considered to be a
measure of success for an entrepreneurial businesses.
Firstly, high growth enterprises contributed more to economic growth than micro
enterprises in the start-up phase (Wong et al., 2005). Secondly, a large proportion of
Owner/Managers undertaking business start-up had no growth aspirations. Hay and
Kamshad (1994) noted such enterprises often remained constant in size as their existence
provided lifestyle advantages for Owner/Managers. Such enterprises typically had minimal
ambition beyond maintaining their current operations and providing their products and
services within existing markets (Levy et al., 2005).
Thirdly, Hessels et al. (2008) noted a deficiency of research exploring the diversity of
entrepreneurs with a growth perspective. Therefore, it is essential entrepreneurial education
enables existing and nascent entrepreneurs to pursue an entrepreneurial career with a growth
perspective. Failure to enable this could mean graduate start-up with non-growth aspirations
and limited potential.
Confidence (Cnfdnc): The current interest in entrepreneurship is apparent by its high
visibility within the UK media, through programmes such as “Dragons Den” and the
“Apprentice” and government policies to encourage entrepreneurial activity (Levie et al.,
2010). In the UK, increased provision and focus upon entrepreneurial education within the
primary, secondary, further and HE sectors increases individual entrepreneurial orientation
(Frank et al., 2005) and the confidence on the attainability of such a career (Han and Lee,
1998; Russell et al., 2008). Higher entrepreneurial competency has been associated with self-
11
confidence and an illusion of control (Koellinger et al., 2007). Thus, entrepreneurial
education must encourage new entrepreneurial careers and increase the confidence of the
existing entrepreneurial population to further develop their activities.
Interests (Intrst): Jaafar and Abdul Aziz (2008) noted nascent entrepreneurs and
Owner/Managers pursue an entrepreneurial career to develop an idea or pursue a hobby. An
entrepreneurial education programme should therefore provide the student with the ability to
generate new enterprise ideas (DeTienne and Chandler, 2004) and refine and develop existing
proposals (Politis, 2005).
Qualifications (Qlfctns): Prior research informs us that SME Owner/Managers have
lower formal educational levels in comparison to their counterparts within larger businesses,
and participate in fewer training activities (OECD, 2002; Bartram, 2005). In contrast,
Robinson and Sexton (1994) suggest SME Owner/Managers are more highly educated than
the general public, a statistic supported by Muir et al. (2001) based on a study of female
entrepreneurs.
Schwarz et al. (2009) noted highly educated entrepreneurs were more likely to grow
their enterprises than lesser qualified counterparts. Moreover, the importance of highly
educated Owner/Managers for the survival and growth of business start-ups is well
established (Cooper et al., 1994; Kennedy and Drennan, 2001). Therefore, an educated and
skilled labour force is considered essential for the growth of the SME sector within the global
economy (Walker et al., 2007). Thus, it is important to assess the importance the individual
student places on the attainment of an entrepreneurial related qualification as a mechanism to
develop their entrepreneurial competencies.
In addition to motivational characteristics for undertaking entrepreneurial education, it
is also important, however, to examine how these are related to students’ future career
aspirations for both self-employment and employment opportunities post programme of study.
12
Levesque et al. (2002) recognised the significant differences between self-employment and
employment careers in terms of income, work required, risk and independence. McMullen et
al. (2008) identified the motivation to become an entrepreneur is closely associated with
levels of government related economic freedom.
As a consequence, it is possible to identify opportunity motivated entrepreneurship
(OME) and necessity motivated entrepreneurial (NME) activity. The authors recognise OME
as when individual/s undertake a business start-up having recognised a business opportunity
and are compelled into the career move by the attractiveness of the opportunity. NME by
contrast, is a last resort, whereby individuals are driven towards an entrepreneurial career
choice through lack of an alternative option (McMullen et al., 2008). The significance of
these aspirations is now considered: -
Self-employed (SE): Several studies have recognised entrepreneurship education can
promote entrepreneurship as a potential alternative career option for graduates post-
graduation and encourage favourable attitudes towards entrepreneurship (Katz, 1991;
Kolvereid and Moen, 1997; Young, 1997; Alvarez and Jung, 2003; Jones et al., 2008). There
remains an on-going challenge, however, to inform and convince undergraduate students
regarding the viability and sustainability of self-employment through a business start-up as an
alternative career to employment (Carayannis et al., 2003; von Graevenitz et al., 2010).
Schwarz et al. (2009) identifies three underlying drivers for self-employment, namely:
i) Educated entrepreneurs are expected to create business start-ups which grow more
effectively than their lesser educated equivalents.
ii) Increased global competition has reduced the attractiveness and opportunities for wage
employment in larger organisations.
iii) Increase in graduate unemployment.
13
They further note it is not known whether environment or individual motivational
characteristics drive students’ career decisions toward self-employment. Therefore, this
study explores the relationships between motivational characteristics for entrepreneurship
education and career aspirations towards self-employment of undergraduate students
pursuing a degree in entrepreneurship.
Employed (E): Seeking appropriate waged employment has long been regarded as
the optimum graduate ambition post study (Nyaribo et al., 2012; Teichler, 2012). Tan et al.
(1995) proposed, however, that students may be attracted to entrepreneurial learning as a
vehicle towards an alternative career opportunity in times of economic recession and high
graduate unemployment. Thus, intention to undertake both entrepreneurial activity and
entrepreneurial education could be heavily influenced by economic climate, which is
particularly relevant in the current global climate (Rae, 2007; Schwarz et al., 2009).
Alternatively, waged employment can also be a pre-cursor to future entrepreneurial activity
to acquire the relevant qualities, skills, experience and knowledge for future success.
Moreover, Carter (1998: 233) found in her study of alumni perceptions of entrepreneurship
education in HE that many:
‘…believed it was important to gain some work experience prior to start-up as it not only
gave them detailed sectoral knowledge, it also provided a network of business contacts
and the appropriate finance to start-up.’
Young (1997), also noted, however, that students might study entrepreneurship if they
wish to acquire knowledge beneficial to their career in a larger organisation. Holden et al.
(2007) suggest that there remain serious deficiencies regarding information about the SME
graduate labour market. Henley (2007) therefore stressed the importance for enterprise
education providers to prepare aspiring entrepreneurs for undertaking new business start-ups.
Thus, it seems the motivations of students to achieve employment having studied
14
entrepreneurial education varies significantly and warrants further investigation. Following,
from this discussion, the Figure 1 conceptualises the analysis approach undertaken in this
study.
See Figure 1 here
Following on from investigation of the relationship of certain motivation characterises
towards future career aspirations, three specific research questions are constructed, upon
which the study will undertake its analysis.
RQ1 - Evaluate the different levels of relevance between the motivation characteristics of
students, and their future career aspirations to employment or self-employment (within 12
months after completion).
RQ2 - Evaluate the relative evidence of the considered different levels of importance of the
motivation characteristics to the different future career aspirations?
RQ3 - Evaluate how gender and age of a candidate student may contribute to the ways the
different motivation characteristics impact on their future career aspirations?
Design/methodology/approach
The research utilised a multi-method approach to data collection for the purposes of
triangulation and to take advantage of the respective qualities of quantitative research
instrumentation (Mingers, 2001). The first stage involved the analysis of student enrolment
data to identify age, gender and background characteristics such as employment status and
qualifications to enable respondents profiling. The second stage involved structured
interviews using a questionnaire with all the students undertaking the course to discover why
they had chosen to embark on an undergraduate enterprise degree. The sample reflected the
age and gender differences identified in the enrolment data.
The rationale for analysing these differences was based on the findings of previous
studies. For example, it is widely acknowledged that gender has a significant effect upon
15
nascent entrepreneurship (Brush, 1992, Minniti et al., 2005) and there is considerable
variation in entrepreneurial activity between different age groups (Davidsson and Honig,
2003; Reynolds et al., 2003).
For example, Allen et al. (2007) identified levels of female entrepreneurial activity in
the UK (10.73%) were found to be inferior (7.72%) in both early stage (male 11.98%,
female 7.25%, 3.73%) and established enterprises (male 6.47%, female 3.48%, 2.99%) to
male business-owners (18.45%). For the purposes of this study, GEM age groupings were
utilised (Bosma and Harding, 2006). Prior to the interview, students were provided with an
interview guide asking them to consider why they had selected the course and what they
considered to be the primary motivations behind the decision to study the undergraduate
enterprise programme. Interviews were either conducted in person or by telephone. The
average length of an interview was 30 minutes.
During the interview, students were asked to complete a structured research
instrument employing five-point Likert arrays to enable statistical and comparative analysis
(see Table 1).
See Table 1 here
The Likert arrays were designed to assess the importance of each of the motivational
characteristics identified previously underpinning their desire to undertake an
entrepreneurship programme. The scale runs from one as “Not Important” to five as “Most
Important” motivational characteristic. In addition, students were asked to identify whether
they wished to pursue a career in employment or self-employment post-graduation. All
students taking the course had to complete the interview process as part of their application
process with no exemptions allowed.
Because of the nature of the data, non-parametric techniques were deemed to be a
pertinent choice of analysis approach in this study. As mentioned previously, certain
16
advantages of the use of a non-parametric approach include the relaxing of the need for
Gaussian distributed data values, as well as the ability in this case to investigate non-linear
relationships between the motivational characteristics and future employment aspirations.
The non-parametric technique utilised in this study is the CaRBS technique,
introduced in Beynon (2005a; 2005b), see Appendix A for a technical description of the
technique. Since its introduction the CaRBS technique has been applied in the areas of:
public administration (Beynon and Kitchener, 2005), medicine (Beynon et al., 2006a, Beynon
et al. 2006b), animal biology (Beynon and Buchanan, 2004), E-learning (Jones and Beynon,
2007) and strategy (Beynon et al., 2010). In the CaRBS technique there is the allowance for
an a priori considered non-certainty of the association of motivational characteristics to the
student aspiration problem considered. Given this non-certainty, CaRBS also allows a visual
exposition of the relationships between the “dependent” and potential “contributory”
variables in order to allow identification of whether the relationships were linear or non-
linear in nature. Further, using CaRBS, there is a direct understanding of the quality of the
Likert scale based information with respect to each considered motivational characteristic, in
terms of whether there was no information present in Likert scores, or whether there was
evidence pertaining to their future career more aspirations to employment or self-employment
(see figures presented later).
Participants
A total of 720 students enrolled onto the EU funded undergraduate enterprise degree
programme in the Objective One areas of Wales including north, mid, east, west and south
Wales during the period of investigation, of which 383 (53%) were female and 337 male
(47%), with an age range from 19 to 64 years old. The programme was managed by the
University of Glamorgan and delivered through a Further Education network throughout
17
Wales. The mean age for the cohort was 37.37 with a marginal difference in the gender mean
ages (see Table 2). The profile of such students can be considered as non-traditional to typical
HE undergraduate students in terms of age range, and also provides a student population that
also differs in terms of age with those traditionally analysed with regards to enterprise
education. The purpose of the programme was to develop entrepreneurial knowledge and
skills, and thereafter business start-up, development and growth activity.
See Table 2 here
Further, using the age ranges, 18-24 (later labelled 1), 25-34 (2), 35-44 (3), 45-54 (4)
and 55-64 (5), Figure 2 presents a breakdown of the percentage of students (from the 720), in
each of these age groups.
See Figure 2 here
CaRBS Analysis of Student Motivation Data Set
As highlighted earlier, the contention in this study is the use of the CaRBS technique offers a
number of advantages over the employment of alternative traditional techniques, such as
logistic regression. First, by drawing on all the available information to model student
aspirations, evidence-based approaches can accommodate outliers within datasets without
needing to fit them to a Gaussian distribution by weighting them or excluding them from the
analysis altogether.
Second, because evidence-based approaches are data-driven they are also able to
reveal the full range of linear and non-linear relationships which might be present within a
dataset. Throughout the study, there is emphasis on the visual representation of results, and
relevance and contribution of the motivational characteristics describing the students and how
they may evident their future career aspirations (employment or self-employment).
18
The disadvantage of CaRBS is that it does not allow a statistical significance
equivalent to be calculated and thus the research design is not able to meet the usual
conditions necessary to establish broad statistical representativeness as identified, for
example, by Storey (2002). Standard hypotheses are also, therefore, not applicable to this
study, which therefore positions this study as an initial exploration of a case study utilising
key research questions. This also limits the generalizability of the specific results beyond the
population of students undertaking the enterprise programme used in the study. Because the
purpose of the research was to begin to identify relationships between motivations for
entrepreneurship education and aspiration to self employment, however, this is not seen as a
disadvantage, given that the study itself can be seen to be a case study (partly because of the
non-traditional age range of the students) and because of the other advantages of the CARBS
technique.
The CaRBS based analysis undertaken here is the modelling of the students’
motivational characteristics in re-creating their expressed aspirations, labelled here as either,
employment (E defined here the hypothesis x - see Appendix A) or self-employment (SE
defined not-the-hypothesis ¬x). The configured CaRBS system produces a final aspiration
body of evidence (BOE) for each student, represented as a simplex coordinate in a simplex
plot (the standard classification domain employed with CaRBS), made up of an equilateral
triangle, whose base vertices in this case are the two aspirations {SE} and {E}, and the top
vertex represents ignorance (termed here as {E, SE}).
Analysis and Results
The emphasis here is on the relevance and contribution of the individual motivational
characteristics in this modelling process (configuring a CaRBS system). Furthermore, how
“discerning” were the individual Likert scale based responses from the students to the
19
respective motivation questions, when they were employed to segment the known aspirations
of the students, see Figure 3 (With a grey shaded sub-region of the simplex plot domain
shown - see the small full simplex plot domain for reference). In other words, to what extent
were the motivations to undertake the course related to their future employment or self-
employment aspirations
See Figure 3 here
In Figure 3, for each of the known aspirations, SE (self-employed) and E (employed),
the simplex coordinate forms of the respective average motivation BOEs are presented (see
Appendix A), representing evidence from the motivational characteristics, to the students’
predicted positions in terms of the employment, self-employment and ignorance domain. The
lines joining the pairs of SE and E simplex coordinates are to enable comparisons between
the segmenting strengths of the individual motivational characteristics. There are two
positional issues to consider when viewing the results in Figure 3 (and considered in
conjunction with each other);
i) Vertical distance from the {E, SE} vertex: The further distance away (down) from the {E,
SE} vertex the less “ignorance” there is associated with the evidence from the
motivational characteristic in the overall segmentation of students’ aspirations (i.e. the
motivational characteristic is more relevant to the aspiration).
ii) Horizontal distance between SE (Self-employment) and E (Employment) labelled simplex
coordinates associated with a motivational characteristic: the horizontal distance between
the two points considers the level of “ambiguity” of the responses made between the
groups of differently aspiring students (more distance between them infers less ambiguity,
and a stronger power of the motivational characteristics to “explain” differences between
the employment or self-employment aspirations). Based on these two positional
20
aspirations, there are three groups, in contribution terms, of motivational characteristics
shown (based on distance down the simplex plot sub-domain).
The most relevant are the group of motivational characteristics, Start-Up (StrtUp),
Confidence (Cnfdnc) and Qualifications (Qlfctns). This is followed by the group
Management (Mngmnt) and Interest (Intrst). Finally, nearest the {E, SE} vertex is Growth
(Grwth), which exhibits the least relevance in this analysis.
In terms of the level of ambiguity in the evidence from these motivational
characteristics, Qualifications, with the greatest distance between SE and E simplex
coordinates has the least ambiguity in its evidence. In more “Traditional” terms, the
interpretation is that the most influential motivational characteristics underpinning the
application to study entrepreneurship education and related to the employment or self-
employment aspirations, were the urge to achieve a qualification, desire to undertake a
business start-up and increase self-confidence.
Less influence was awarded to the acquisition of managerial experience and to
increase interest in the subject matter. Least influence was awarded to the issue of achieving
business growth. Thus, it was apparent that student responses related to employment or self-
employment aspirations were focused on the shorter term obtainable motivations with the
completion and attainment of the qualification, increasing subject knowledge and confidence
and thereafter the immediate prospect of business start-up. There was however, minimal
consideration of the concept of business growth to the entrepreneurship student which might
have been considered as a longer term and hence more unobtainable objective of
entrepreneurship study.
Beyond the identification of the most or least relevant motivational characteristics,
further identification of the type of influence (e.g. positive or negative, linear or non linear) of
the individual motivational characteristic responses to the employment or self-employment
21
aspiration question is next given by demonstrating the direct association of the response
given and the evidence it contributes to the classification of the students (item response to
motivation BOE), see Figure 4 (these graphs are made up of a combination of the graphs A1a
and A1b in Figure A1). That is, for an individual motivational characteristics, was their
relevance, as the importance of a motivational characteristics increases for a student (from
‘Not’ to ‘Most’), because the students had aspirations towards either employment or self-
employment (that which could be discerned in the CaRBS analysis of course).
See Figure 4 here
In Figure 4, each graph shows ‘up to’ three mass values which make up a motivation
BOE, which offer belief-termed evidence to a student’s aspirations being employment
(mj,StrtUP({E}) for example in Figure 4a for Start-Up motivational characteristic) or self-
employment (mj,StrtUP({SE})) and between these ignorance (mj,StrtUP({E, SE})). These mass
value lines are a direct consequence from merging the first two graphs in Figure A1 in
Appendix A, which exposit the stages of the construction of motivation BOEs, prior to their
representation in a simplex plot. Moreover, the points are the actual BOE mass values
associated with the Likert scale (‘Not’ - 1 to ‘Most’ - 5) values employed in this study, with
the lines joining them showing the general structure of the mass values in each motivation
BOE (over a continuous domain from ‘Not’ to ‘Most’).
Interpreted more qualitatively, for example referring to the Start-Up motivational
characteristic (in Figure 4a), the CaRBS analysis suggests that a response from ‘Not’ up to
‘Contributory’ levels of motivation shows constant evidence towards the respondent having
aspirations to being employed (mj,StrtUP({E})), whereas, from ‘Important’ to ‘Most’ the
evidence towards employment aspirations reduces, with an initial increase in ignorance
(mj,StrtUP({E, SE})) then evidence towards the respondent having aspirations to being self-
employed (mj,StrtUP({SE})).
22
In summary, there appears to be a positive, ‘non-linear’ relationship with increasing
importance of the Start-Up motivational characteristic and an increasing association to their
future career aspiration of self-employment (and so away from employment). Students with a
self-employment aspiration were thus positively related to the business Start-Up motivational
characteristic. Referring back to Figure 3, demonstrates also that this motivational
characteristic is one of the three most relevant considered. Whilst self-explanatory, this
provides supporting evidence of the positive relationship between an immediate
entrepreneurial aspiration, via self-employment and a business start-up motivation for taking
the course.
Considering the other two most relevant motivation characteristics, Confidence
(Cnfdnc - Figure 4d) and Qualifications (Qlfctns - Figure 4f), in Figure 4d, a similar positive
relationship is also shown between the increasing level of importance of responses to the
contribution of the Confidence motivational characteristic and a student’s associated
aspiration towards self-employment (increased contribution resulting is reduced evidence
towards employment and/or increased evidence towards self-employment). Similarly, in
Figure 4f, there is a positive relationship shown for the responses to the contribution of the
Qualification motivation to a student’s aspiration to being in self-employment.
These results also, however, demonstrate the non-linear facet of the analysis
undertaken when using the CaRBS technique. While a linear set of values were initially
attached to the linguistic response values ‘Not’ to ‘Most’, the graphs in Figure 4 show the
non-linear set of evidences they offer in this problem, for each motivational characteristic.
The CaRBS analysis can go further than elucidating potential non-linear relationships. A
unique feature of the employment of CaRBS, is there can also exist only total ignorance in
the evidence from some responses. For example, in Figure 4c (Grwth motivation), for the
responses ‘Not’ to ‘Contributory’ there is only ignorant evidence from these response levels,
23
meaning the responses at these levels were too ambiguous to both student self-employment
and employment aspirations to enable any specific relational evidence from them. At the
higher levels of motivation, however, there is some evidence that the growth motivation is
positively related to self-employment.
For the other motivational characteristics, the evidence is also of potential non–linear
relationships regarding the importance of them towards future career aspirations of
employment or self-employment. For example, for Management, as its contribution
importance begins to increase then this is related to a fall in the aspiration towards
employment, with no relationship (ambiguity) at the point where the response value
‘Contributory’, and then, as this motivation’s importance increases towards its highest value
of ‘Most’ becomes a positive relationship with the self-employment aspiration.
Conversely, for the motivational characteristic of Interest in the subject, as the
motivation importance increases, the self-employment aspiration falls, with no relationship at
the point where the motivation become ‘Contributory’, and then as the motivation importance
increases towards its highest value becomes a positive relationship with the employment
aspiration. This was the only motivational characteristic where there was more contributory
evidence towards an employment aspiration. This result suggests that interest in the
entrepreneurship subject matter does not contribute to a self-employment career choice as an
initial student motivator towards programme choice.
Influence of Motivation Characteristics with other Demographics
This section considers the exposition of the relevancies of the considered motivational
characteristics in the aspirations of students to self-employment or employment with regard
to their relevance when taking into account gender and age demographics. The prior
literature has suggested demographics, such as gender and age, impact significantly upon
24
entrepreneurial motivations and different career aspirations including employment or self-
employment. Therefore, it is a logical progression to investigate the relevance of such
demographics against motivational characteristics of the desire to undertake entrepreneurial
education. This analysis will inform the construction and provision of effective
entrepreneurship education programmes based on understanding learning requirements of
specific student types. The emphasis on the graphical elucidation of the demographic based
relevancies continues here, in each of the following presented subsections. Further, analysis
is only undertaken on the three most relevant motivation characteristics (see Figure 3),
namely Start-Up, Confidence and Qualifications.
Gender: This section examines the impact of gender on student entrepreneurial motivational
characteristics contrasted against future career aspirations towards employment or self-
employment. The prior literature has clearly highlighted variances in entrepreneurial uptake
by gender (Minniti et al., 2005; Allen et al., 2007). Therefore, it is important to assess the
variances in gender attitudes towards entrepreneurial education. Considering this gender
demographic, Figure 5 provides a constellation breakdown of certain motivational
characteristics.
See Figure 5 here
The details presented in Figure 5, are described with reference to the Confidence
(Cnfdnc) motivation characteristic. Near the base of the simplex plot sub-domain shown (to
the left), the constellation breakdown is made up of the original solid line connecting the
average motivation BOEs for students with employment (E) and self-employment (SE)
aspirations (shown with small circles). From these small circles, there are four dashed lines,
with respective ‘end’ circles representing the average motivation BOEs for all male/female
employment/self-employment aspiring respondents (labelled M and F appropriately). The
25
consideration here is, in what directions are the respective end circles (labelled M or F), in
relation to the respective E or SE circle. For ease of explanation, the terms SE-M, SE-F, E-M
and E-F represents these paths, for example, SE-M are male students with aspirations to self-
employment, etc.
For the Confidence motivational characteristic, in the case of those students with
known employment aspirations, the female students (E-F), based on their motivational
characteristic responses, were more associated with the employment aspiration than their
male counterparts (the E-F path is nearer the {E} vertex than the E-M path).
Similarly, those students with self-employment aspirations, the female students, based
on their motivational characteristic responses, are more associated with the self-employment
aspiration than their male counterparts (the SE-F path is nearer the {SE} vertex than the SE-
M path). With respect to both aspiration intentions, employment and self-employment, it was
apparent female students, whether aspiring for employment, or self-employment, were more
discerning in their responses to the respective motivational characteristic question. In the
case of those aspiring for self-employment, this would take the form of them indicating more
confidence in the option of an entrepreneurial career than their male counterparts. This
reinforces the need to provide female students with appropriate female entrepreneurial role
models to encourage them to consider an entrepreneurial career option.
This is perhaps unsurprising as the literature suggested males have more confidence to
undertake a business start-up than their female counterparts (Allen et al., 2007). In the case of
the Qualifications and Start-Up motivational characteristics, the differences of the E-F and E-
M paths (and SE-F and SE-M) are less apart than in the case with the Confidence motivation
characteristic, indicating not as noticeable differences between the genders on these
motivational characteristics. However, even though to a lesser extent than the confidence
motivational characteristic, while the females with aspirations towards employment were
26
most consistent in their responses to the Qualifications and Start-Up motivation questions, it
was the males who were more consistent in the responses when having aspirations towards
employment.
Age: The annual GEM studies (e.g. Allen et al., 2007) identified differing levels of
entrepreneurial aspiration by age, with aspiration more prevalent in the 25-34 and 35-44 age
groups, but less significant in the 18-24 grouping. It is essential entrepreneurship education
providers effectively target the 18-24 grouping to encourage further uptake of
entrepreneurship education and thereafter business start-up activity. Considering this age
demographic, Figure 6 shows a constellation breakdown of certain motivation characteristics.
See Figure 6 here
From Figure 6, considering the confidence motivation (Cnfdnc), for those students
with self-employment aspirations, there is a general trend of the older the student (in age
groups 3, 4 and 5 - described in Figure 2), being more associated with the self-employment
aspiration than the younger aged students (in age groups 1 and 2). That is, for Cnfdnc, the
simplex coordinates SE-3, SE-4 and SE5 are nearer the {SE} vertex than the SE-1 and SE-2.
The argument regarding this evidence is that the older age groupings, students over the age of
35, might require greater self-confidence to realise the opportunity offered by self-
employment based on their prior working and life experiences. Thus undertaking an
entrepreneurship education course offers the opportunity for students to build confidence in a
safe environment. Similar, inference can be gauged from inspection of the other
constellations presented in Figure 6.
27
Discussion and Conclusions
This study has presented a unique evaluation of student motivations to undertake an
entrepreneurship education programme using the novel CaRBS data mining technique,
generating a number of contributions to the literature. The study confirmed RQ1 in that it is
possible to discern different levels of relevance between motivation characteristics of
students and their future aspirations towards employment or self-employment. The analysis
also revealed the key motivators to entrepreneurship education in this instance were (in the
discerning of students with employment and self-employment aspirations):
i) Desire to achieve a qualification.
ii) Desire to undertake a business start-up.
iii) Desire to increase confidence in the option of an entrepreneurial career.
These results are consistent with the findings of Young (1997) and Galloway and
Brown (2002), suggesting students pursue entrepreneurial education programmes to acquire
additional skills and knowledge, independence and increased confidence through an
entrepreneurial career. Less prevalence was awarded, however, to the desire to develop
interest in the subject matter or the need to acquire managerial experience. This result
conflicts somewhat with the views posited by DeTienne and Chandler (2004) and Politis
(2005), which suggested entrepreneurial education programmes provide the opportunity to
develop subject knowledge. The least relevant motivational characteristic was identified as
the desire to undertake an entrepreneurial education programme to achieve business growth.
This result may suggest that the students surveyed either did not value or did not understand
the significance of business growth, as proposed by Acs and Audretsch (2003), Audretsch
and Keilbach (2006) and Praag and Versloot (2007) as an important consideration when
contemplating an entrepreneurial qualification.
28
From these results, it could be interpreted, therefore, that the entrepreneurial
education students surveyed give greater significance to issues of immediate importance to
them like achieving the qualification, building confidence and thereafter considering self-
employment. If such motivational attitudes were to be maintained for those undertaking a
business start-up then there may be a danger that these Owner/Managers may not pursue a
growth strategy and simply operate as lifestyle non-growth enterprises, as previously
recognised by Levy et al. (2005). It is essential such a mindset be avoided and young nascent
Owner/Managers informed regarding the importance of a more strategic mindset and greater
growth orientation.
This also suggests that enterprise education providers may need to give consideration
to informing and educating students regarding the importance of business growth from the
outset of the programme. Beyond the general results of the relevance of particular
motivational characteristics, the CaRBS technique has also allowed some inference to be
gauged on different cohorts of students, namely using their gender and age demographics.
For example, in the case of the gender demographic, in particular with regard to confidence,
levels of difference were noticed in the relationships between the importance levels of
motivations of male and female students and the self-employment or employment aspirations.
The motivations for entrepreneurial activity previously identified by Roberts (1991),
Galloway and Brown (2002), Segal et al. (2005) and Taormina and Lao (2007) as need to
achieve, desire for independence, dissatisfaction with current employment bear direct
comparison with the motivations for entrepreneurial education, for example, desire for
independence and self-improvement with the obvious exception of desire to achieve
qualifications.
With regard to RQ2, the study found it was possible to discern the relative evidence of
the considered different levels of importance of the motivation characteristics to the different
29
future career aspirations. Students with a self-employment aspiration were positively related
to the business Start-Up motivational characteristic. This finding confirms the ability and
accuracy of CaRBS to associate motivational characteristics to career aspiration.
Finally, with regard to RQ3, the study confirmed how the gender and age of a
candidate student impacted upon the different motivation characteristics towards future career
aspirations. The study found that female students were more discerning in their responses
regarding motivational characteristics than their male counterparts. This suggests that it is
possible using techniques as CaRBS to understand the learning requirements of students prior
to the course and provide customised learning programmes which could be gender specific.
Furthermore, the analysis suggested that older students were more associated with self-
employment aspirations although this required enhanced confidence from their programme to
enable this to occur. This evidence again informs the extant knowledge in that the learning
requirements of mature students differ from their younger counterparts and thus require
different support and instruction with greater focus on operationalising the process.
This study also contributes to methodology. First, it investigates motivations for
undertaking entrepreneurship education using a novel data analysis technique (CaRBS)
allowing a fuller analysis of the dataset than more traditional techniques (though within the
statistical restrictions also imposed by CaRBS in terms of the lack of tests for statistical
representativeness). The CaRBS method enables inclusion of data outliers not permitted with
standard regression data analysis techniques thus providing a more accurate representation of
student motivations towards entrepreneurship programmes. Secondly, it provides new
insights into motivations for undertaking an entrepreneurship education programme with
regard to self-employment or employment aspirations. Finally, the study considers non-
traditional learners which have not been previously represented within the extant literature,
30
illustrating the strength of CaRBS within a case study context in which a data mining
approach is deemed most appropriate.
In terms of the future utilisation of the employed CaRBS technique, in the area of
entrepreneurial education, it could potentially provide an ability to generate enhanced
understanding of the pedagogical requirements and course content of individual students. The
CaRBS technique could specifically offer an alternative to other statistical analysis
techniques within the entrepreneurship discipline, where the data is non parametric, the
dataset can be seen as a case study comprising the population under investigation, and the
issue being researched requires a data mining type approach. Finally, the study generates
knowledge which may fit the definition of having practical implications and informing the
effectiveness of programme design and increase OME within the student group (McMullen et
al., 2008) for educators, programme providers and policy makers. As such it could make a
contribution to practice in a number of ways.
As way of an example, customized programmes of studies could be constructed,
which may offer more specialised focuses, such as on Confidence and/or Start-Up (two
motivational characteristics found here to be particularly relevant in discerning those students
with self-employment and employment aspirations). Entrepreneurial personality exercises
could also be used to further assess the student’s personality and current skills set. Thereafter,
this information could be used to identify strengths and weaknesses and a development plan
for personal improvement identified to build confidence and entrepreneurial competency.
Moreover, the findings suggest the need for dedicated programme modules which
would enable a business start-up, preferably providing seed-corn funding to assist this
process. For entrepreneurship education providers and policy makers, it could potentially
influence the selection of more entrepreneurially oriented individuals with specific
31
orientation towards business start-up and enable the construction of more student focused
programmes of study.
Appendix A
This appendix outlines the rudiments of the CaRBS technique used in this study (Author,
2005a; 2005b). When used as a classification tool, it undertakes the predicted classification
of objects (students here) based on a number of characteristics (Likert based question
responses student’s motivation of entrepreneurship education). The rudiments of CaRBS are
based on Dempster-Shafer theory (Dempster, 1968; Shafer, 1976), the evidence from a
characteristic value is quantified in a body of evidence (BOE), denoted by m(), where all
assigned mass values sum to unity.
Moreover, for a student oj (1 j nO) and their ith motivational characteristic value ci
(1 i nC), a motivation BOE defined mj,i(), has mass values mj,i({x}) and mj,i({x}), which
denote levels of exact belief in the classification of a student to a hypothesis x (employment
aspiration) and not-the-hypothesis ¬x (self-employment aspiration), and mj,i({x, x}) the level
of concomitant ignorance, given by:
mj,i({x}) = max(0, i
iii
i
i
A
BAvcf
A
B
1)(
1), mj,i({x}) = max(0,
ii
i
i BvcfA
B
)(
1)
and mj,i({x, x}) = 1 mj,i({x}) mj,i({x}),
where cfi(v) = )(
1
1ii vk
e
, and ki, i, Ai and Bi are incumbent control variables. Figure A1
presents the progression from a value v to a motivation BOE and its representation as a
simplex coordinate in a simplex plot.
See Figure A1 here
In Figure A1, a question response value v is first transformed into a confidence value (A1a),
from which it is de-constructed into its motivation BOE (A1b), made up of a triplet of mass
values mj,i({x}), mj,i({x}) and mj,i({x, x}). Stage (A1c) shows a BOE mj,i(·); mj,i({x}) =
νj,i,1, mj,i({x}) = νj,i,2 and mj,i({x, ¬x}) = νj,i,3 can be represented as a simplex coordinate (pj,i,v)
in a simplex plot (equilateral triangle), such that the least distance from pj,i,v to each of the
sides of the equilateral triangle are in the same proportion to the values vj,i,1, vj,i,2 and vj,i,3.
The set of motivation BOEs {mj,i(), i = 1, …, nC} associated with the business oj can
be combined using Dempster’s combination rule into an aspiration BOE, defined mj().
32
Moreover, using ijm , () and kjm , () as two independent motivation BOEs, ][ ,, kjij mm ()
defines their combination, given by:
}))({})({})({})({(1
}),({})({}),({})({})({})({})]({[
,,,,
,,,,,,
,,xmxmxmxm
xxmxmxxmxmxmxmxmm
kjijkjij
kjijijkjkjij
kjij
,
}))({})({})({})({(1
}),({})({})({}),({})({})({})]({[
,,,,
,,,,,,
,,xmxmxmxm
xxmxmxmxxmxmxmxmm
kjijkjij
ijkjijkjkjij
kjij
,
})]({[})]({[1}),]({[ ,,,,,, xmmxmmxxmm kjijkjijkjij .
This process is then used iteratively to combine the motivation BOEs into an
aspiration BOE. For a student oj, its aspiration BOE contains the information necessary for its
final classification (to self-employment or employment aspiration). To illustrate the method
of combination employed here, in Figure 1c, the combination of two example BOEs, m1()
and m2(), is shown graphically in a simplex plot to a new BOE denoted mC().
The configuration of a CaRBS system depends on the assignment of values to the
incumbent control variables (ki, i, Ai and Bi, i = 1, …, nC). With the question responses
labelled 1 to 5 and then standardised, the domains of the control variables are set as; –3 ki
3, –2 i 2, 0 Ai < 1 and Bi = 0.6 (see Author, 2005b). The evaluation of specific control
variable values is solved here using an evolutionary algorithm called Trigonometric
Differential Evolution (Fan and Lampinen, 2003), with operation parameters; amplification
control F = 0.99, crossover constant CR = 0.85, trigonometric mutation probability Mt = 0.05
and number of parameter vectors NP = 10 number of control variables = 180.
Associated with any evolutionary algorithm is an objective function (OB), here a
positive function which measures the misclassification of students from their known defined
categorized aspiration (self-employment or employment). The equivalence classes E(x) and
E(x) are sets of objects known to be classified to {x} and {x}, respectively. The
subsequent OB is given by:
)()(
}))({})({1(|)(|
1)})({})({1(
|)(|
1
4
1
xEojj
xEojj
jj
xmxmxE
xmxmxE
.
which has the range 0 OB 1. The division of elements of OB by |E()| takes account for
unbalanced data sets, in this case with different numbers of students to the two aspirations of
self-employment and employment.
An indication of the evidential support offered by each question to the known self-
employment and employment aspiring students is made with the evaluation of average
33
motivation BOEs. More formally, for those students in an equivalence class E(), the average
motivation BOEs, defined ami,(), is given by:
ami,({x}) = )(
,
|)(|
})({
Eo
ij
jE
xm, ami,({¬x}) =
)(
,
|)(|
})({
Eo
ij
jE
xm, ami,({x,¬x}) =
)(
,
|)(|
}),({
Eo
ij
jE
xxm
where oj is a student. As BOEs they can be represented as simplex coordinates in a simplex
plot describing the evidential support of a motivation based question to the aspiration of the
students.
REFERENCES
Acs, Z. J., and Audretsch, D. B. (2003), “Innovation and technological change”. In: Acs Z. J.,
Audretsch, D.B. (Eds.), Handbook of Entrepreneurship Research, Kluwer Academic
Publishers, Boston, pp. 55-79.
Allen, I. E., Elam, A., Langowitz, N. and Dean, M. (2007), Global Entrepreneurship Monitor
2007 Report on Women and Entrepreneurship, Global Entrepreneurship Monitor.
Alvarez, R. D. and Jung, D. (2003), “Educational curricula and self-efficacy: entrepreneurial
orientation and new venture intentions among university students in Mexico”, Frontiers of
Entrepreneurship Research, Babson-Kaufman Research Conference Proceedings, Babson
Park, MA.
Anderson, A. and Jack, S. (2008), “Role Typologies for enterprising education: the
professional artisan?”, Journal of Small Business and Enterprise Development, Vol. 15 No. 2,
pp. 259-273.
Audretsch, D. and Keilbach, M. (2006), Entrepreneurship, Growth and Restructuring.
Papers on Entrepreneurship, Growth and Public Policy, 2006-13, Max Planck Institute of
Economics, Entrepreneurship, Growth and Public Policy Group.
Bartram, T. (2005), “Small Firms, big ideas: the adoption of human resource management in
Australian small firms”, Asia Pacific Journal of Human Resources, Vol. 43 No. 1, pp. 137-
154.
Basu, A. and Goswami, A. (1999), “South Asian entrepreneurship in Great Britain: factors
influencing growth”, International Journal of Entrepreneurial Behaviour and Research, Vol.
5 No. 5, pp. 251-275.
Beynon, M. J (2005a.), “A Novel Technique of Object Ranking and Classification under
Ignorance: An Application to the Corporate Failure Risk Problem”, European Journal of
Operational Research, Vol. 167, pp. 493-517.
34
Beynon, M. J. (2005b), “A Novel Approach to the Credit Rating Problem: Object
Classification Under Ignorance”, International Journal of Intelligent Systems in Accounting,
Finance and Management, Vol. 13, pp. 113-130.
Beynon, M. J. and Buchanan, K. L. (2004), “Object Classification under Ignorance using
CaRBS: The Case of the European Barn Swallow”, Expert Systems with Applications, Vol.
27 No, 3, pp. 403415.
Beynon, M. J., Jones, L. and Holt, C. A., (2006a), “A novel approach to the exposition of the
temporal development of post-op osteoarthritic knee subjects”, Journal of Biomechanics, Vol.
39 No. 13, pp. 2512-2520.
Beynon, M. J., Jones, L. and Holt, C. A. (2006b), “Classification of osteoarthritic and normal
knee function using three dimensional motion analysis and the Dempster-Shafer theory of
evidence”, IEEE Transactions on Systems, Man and Cybernetics Series A: Systems and
Humans Vol. 36, pp. 173-186.
Beynon, M. J. and Kitchener, M. J. (2005), “Ranking the ‘balance’ of state long-term care
systems: A comparative exposition of the SMARTER and CaRBS techniques”, Health Care
Management Science, Vol. 8, pp. 157-166.
Beynon, M. J., Moutinho, L. and Veloutsou, C. (2010), “Supermarket choice as a gender
classification problem: An expositional analysis in the presence of ignorance using CaRBS”,
European Journal of Marketing, Vol. 44 No. 1-2, pp. 267-290.
Bhandari, N. (2006), “Intention for Entrepreneurship among Students in India”, Journal of
Entrepreneurship, Vol. 15 No. 2, pp. 169-179.
Birley, S. and Westhead, P. (1994), “A taxonomy of business start-up reasons and their
impact on firm growth and size”, Journal of Business Venturing, Vol. 9 No. 1, pp. 7–31.
Bosma, N. and Harding, R. (2006), Global Entrepreneurship Monitor, GEM 2006 Summary
Results, Babson and London Business School.
Brooksbank, D. and Jones-Evans, D. (2005), Global Entrepreneurship Monitor: 2005 Wales
Executive Summary Report, National Entrepreneurship Observatory.
Brush, C. (1992), “Research of women business owners: past trends, a new perspective,
future directions”, Entrepreneurship Theory and Practice, Vol. 16 No. 4, pp. 5-30.
Carter, N. M., Gartner, W. B., Shaver, K. G. and Gatewood, E. J. (2003), “The career reasons
of nascent entrepreneurs”, Journal of Business Venturing, Vol. 18 No. 1, pp. 13–39.
Carter, S. (1998), “Entrepreneurship education: alumni perceptions of the role of higher
education institutions”, Paper presented at the 8th Internationalizing Entrepreneurship
Education and Training Conference, European Business School, Schloû Reichartshausen.
Carayannis, E., Evans, D. and Hanson, M. (2003), “A cross-cultural learning strategy for
entrepreneurship education: outline of key concepts and lessons learned from a comparative
35
study of entrepreneurship students in France and the US”, Technovation, Vol. 23 No. 9, pp.
757-771.
Cassar, G. (2007), “Money, money, money? A longitudinal investigation of entrepreneur
career reasons, growth preferences and achieved growth”, Entrepreneurship & Regional
Development, Vol. 19 No. 1, pp. 89–107.
Chell, E. (2001), Entrepreneurship: Globalization, innovation and development, Thompson
Learning, London.
Cho, B. (1998), “Study of the effective entrepreneurship education method and its process”,
Business Education Research, Vol. 2, pp. 27–47.
Chrisman, J. and McMullan, W. (2004), “Outsider assistance as a knowledge resource for
new ventures”, Journal of Small Business Management, Vol. 42 No. 3, pp. 229-244.
Clark, B.W., Davis, C. and Harnish, V. (1984), “Do courses in entrepreneurship aid in new
venture creation?”, Journal of Small Business Management, Vol. 22, pp. 26–31.
Cooper, A. C., Gimeno-Gascon, J. F. and Woo, C. (1994), “Initial human and financial
capital as predictors of new venture performance”, Journal of Business Venturing, Vol. 9 No.
5, pp. 371-395.
Cooper, S., Bottomley, C. and Gordon, J. (2004), “Stepping out of the classroom and up the
ladder of learning; an experiential learning approach to entrepreneurial education”, Industry
and Higher Education, Vol. 18 No. 1, pp. 11-22.
Davidsson, P. and Honig, B. (2003), “The role of social and human capital among nascent
entrepreneurs”, Journal of Business Venturing, Vol. 18 No. 3, pp. 301-331.
Delmar, F. and Davidsson, P. (2000), “Where do they come from? Prevalence and
characteristics of nascent entrepreneurs”, Entrepreneurship and Regional Development, Vol.
12 No. 1, pp. 1-23.
Dickson, P., Solomon, G. and Weaver, K. M. (2008), “Entrepreneurial section and success:
does education matter?”, Journal of Small Business and Enterprise Development, Vol. 15 No.
2, pp. 239-258.
Dempster, A. P. (1967), “Upper and lower probabilities induced by a multiple valued
mapping”, The Annals of Mathematical Statistics, Vol. 38 No. 2, pp. 325-339.
DeTienne, D. and Chandler, G. (2004), “Opportunity Identification and its Role in the
Entrepreneurial Classroom”, Academy of Management Learning and Education, Vol. 3 No. 3,
pp. 242-257.
Dumas, C. (2001), “Evaluation of the outcomes of microenterprise training for low income
women: a case study”, Journal of Developmental Entrepreneurship, Vol. 62 No. 2, pp. 97-
128.
36
Edelman, L. F., Brush, C. G., Manolova, T. S. and Greene, P. G. (2010), “Start-up
Motivations and Growth Intentions of Minority Nascent Entrepreneurs”, Journal of Small
Business Management, Vol. 48 No. 2, pp. 174–196.
Fan, H.-Y. and Lampinen, J. A. (2003), “Trigonometric Mutation Operation to Differential
Evolution”, Journal of Global Optimization, Vol. 27 No. 1, pp. 105-129.
Fayolle, A. (2005), “Evaluation of entrepreneurship education: behaviour performing or
intention increasing?”, International Journal of Entrepreneurship and Small Business, Vol. 2
No. 1, pp. 89-98.
Fayolle, A., Gailly, B. and Lassas-Clerc, N. (2006), “Assessing the impact of
entrepreneurship education programmes: a new methodology”, Journal of European
Industrial Training, Vol. 30 No. 9, pp. 701-720.
Frank, H., Korunka, C., Lueger, M. and Mugler, J., (2005), “Entrepreneurial orientation and
education in Austrian secondary schools: Status quo and recommendations”, Journal of Small
Business and Enterprise Development, Vol. 12 No. 2, pp. 259-273.
Galloway, L. and Brown, W., (2002), “Entrepreneurship education at university: a driver in
the creation of high growth firms?”, Education + Training, Vol. 44 No. 8/9, pp. 398-405.
Galloway, L., Anderson, M., Brown, W. and Wilson, L. (2005) “Enterprise Skills for the
Economy”, Education + Training, Vol. 47 No. 1, pp. 7-17.
Garavan, T. and O'Cinneide, B. (1994), “Entrepreneurship Education and Training
Programmes: A Review and Evaluation – Part 1”, Journal of European Industrial Training,
Vol. 18 No. 8, pp. 3-12.
Gibb, A. (1993), “Enterprise Culture and Education: Understanding Enterprise Education and
its links with Small Business, Entrepreneurship and Wider Educational Goals”, International
Small Business Journal, Vol. 11 No. 3, pp. 11-33.
Gibb, A. (1997), “Small firms’ training and competitiveness: Building on the small business
as a learning organisation”, International Small Business Journal, Vol. 15 No. 3, pp. 13-29.
Gibb, A. (2005), Towards the Entrepreneurial University; Entrepreneurship as a Lever for
Change, National Council for Graduate Entrepreneurship, Policy Paper 3.
Gilad, B. and Levine, P. (1986), “A behavioural model of entrepreneurial supply”, Journal of
Small Business Management, Vol. 24 No. 4, pp. 45-54.
Gilbert, B., Audretsch, D. and McDougall, P. (2004), “The Emergence of Entrepreneurship
Policy”, Small Business Economics, Vol. 22 No. 3-4, pp. 313-323.
Gorman, G., Hanlon, D. and King, W. (1997), “Some Research Perspectives on
Entrepreneurship Education, Enterprise Education and Education for Small Business
Management: A Ten-Year Literature”, International Small Business Journal, Vol. 15 No. 3,
pp. 56-77.
37
Hamidi, D. Y., Wennberg, K. and Berglund, H. (2008), “Creativity in Entrepreneurship
Education”, Journal of Small Business and Enterprise Development, Vol. 15 No 2, pp. 304-
320.
Han, J. and Lee, M. (1998), “A study on the status of entrepreneurship education in Korea
and its direction”, Business Education Research, Vol. 2 No. 2, pp. 5-26.
Harris, M. and Gibson, S. G. (2008), "Examining the entrepreneurial attitudes of US business
students", Education + Training, Vol. 50 No. 7, pp. 568-581.
Harrison, R. and Leitch, C. (2010), “Voodoo institution or entrepreneurial university? Spin-
off companies, the entrepreneurial system and regional development in the UK”, Regional
Studies, Vol. 44 No. 9, pp. 1241-1262.
Hay, M. and Kamshad, K. (1994), “Small firm growth: intentions, implementation and
impediments”, Business Strategy Review, Vol. 5 No. 3, pp. 49-68.
Hayward, G. and Sundes, O. (1997), Evaluating Entrepreneurship Education in Scottish
Universities, University of Oxford, Oxford.
Henley, A. (2007), “Entrepreneurial aspiration and transition into self-employment: evidence
from British longitudinal data”, Entrepreneurship & Regional Development, Vol. 19 No. 3,
pp. 253–280.
Henry, C., Hill, F. and Leitch, C. (2005), “Entrepreneurship Education and training; can
entrepreneurship be taught? Part 1”, Education + Training, Vol. 47 No. 2, pp. 98-111.
Hessels, J., van Gelderen, M. and Thurik, R. (2008), “Entrepreneurial aspirations,
motivations, and their drivers”, Small Business Economics, Vol. 31 No. 3, pp. 323-339.
Hills, G. (1988), “Variations in university entrepreneurship education: an empirical study of
an evolving field”, Journal of Business Venturing, Vol. 3 No. 3, pp. 109-122.
Hisrich, R. D. and Peters, M. P. (1998), Entrepreneurship, McGraw-Hill, Boston.
Holden, R., Jameson, S. and Walmsley, A. (2007), “New graduate employment within SMEs:
still in the dark?”, Journal of Small Business and Enterprise Development, Vol. 14 No. 2, pp.
211-227.
Hytti, U. and O’Gorman, C. (2004), “What is ‘enterprise education’? An analysis of the
objectives and methods of enterprise education programmes in four European countries”,
Education + Training, Vol. 46 No. 1, pp. 11–23.
Hytti, U., Stenholm, P., Heinonen, J. and Seikkula-Leino, J. (2010), “Perceived learning
outcomes in entrepreneurship education: The impact of student motivation and team
behaviour”, Education + Training, Vol. 52 No. 8, pp. 587-606.
Jack, S. and Anderson, A. (1999), “Entrepreneurship education within the enterprise culture:
producing reflective practitioners”, International Journal of Entrepreneurial Behaviour and
Research, Vol. 5 No. 3, pp. 110-125.
38
Jaafar, M. and Abdul Aziz, A. R. (2008), “Entrepreneurship education in developing country:
Exploration on its necessity in the construction programme”, Journal of Engineering, Design
and Technology, Vol. 6 No. 2, pp. 178-189.
Jayawarna, D., Rouse, J. and Kitching, J. (2013), “Entrepreneur motivations and life course,
International Small Business Journal, Vol. 31 No. 1, pp. 34-56.
Johannisson, B., Landstrom, H. and Rosenberg, J. (1998), “University training for
entrepreneurship training – an action frame for reference”, European Journal of Engineering
Education, Vol. 23 No. 4, pp. 477-496.
Jones, P. and Beynon, M. J. (2007), “Temporal support in the identification of e-learning
efficacy: An example of object classification in the presence of ignorance”, Expert Systems,
Vol. 24 No. 1, pp. 1-16.
Jones, P., Jones, A., Packham, G. and Miller, C. (2008), “Student attitudes towards enterprise
education in Poland: a positive impact”, Education + Training, Vol. 50 No. 7, pp. 597-614.
Jones, P., Beynon, M. J., Pickernell, D. and Packham, G. (2013), “Evaluating the impact of
different training methods on SME business performance”, Environment and Planning C:
Government and Policy, Vol. 31 No. 1, pp. 56-81.
Katz, J. (1991), “The institution and infrastructure of entrepreneurship”, Entrepreneurship
Theory and Practice, Vol. 15 No. 2, pp. 85-102.
Katz, J. (2003), “The chronology and intellectual trajectory of American entrepreneurship
education”, Journal of Business Venturing, Vol. 18 No. 2, pp. 283–300.
Kennedy, J. and Drennan, J. (2001), “A review of the impact of education and prior
experience on new venture performance”, International Journal of Entrepreneurship and
Innovation, Vol. 2 No. 3, pp. 153-169.
Koellinger, P., Minniti, M. and Schade, C. (2007), “I think I can, I think I can:
Overconfidence and entrepreneurial behaviour”, Journal of Economic Psychology, Vol. 28
No. 4, pp. 502–527.
Kolvereid, L. and Moen, O. (1997), “Entrepreneurship among business graduates: does a
major in entrepreneurship make a difference?”, Journal of European Industrial Training, Vol.
21 No. 4, pp. 154-160.
Kuratko, D. (2005), “The Emergence of Entrepreneurship Education: Development, Trends,
and Challenges”, Entrepreneurship Theory and Practice, Vol. 29 No. 5, pp. 577-597.
Kuratko, D. F. and Hodgetts, R. M. (2001), Entrepreneurship: A contemporary approach,
Harcourt College Publishers, Fort Worth.
Lange, J. E., Edward, M., Jawahar, A. S., Yong, W. and Bygrave, W. (2011), "Does an
Entrepreneurship education have lasting value? A study of careers of 4,000 alumni,"
39
Frontiers of Entrepreneurship Research, Vol. 31 No. 6, Article 2. Available at:
http://digitalknowledge.babson.edu/fer/vol31/iss6/2.
Levesque, M., Shepherd, D. and Douglas, E. (2002), “Employment or self-employment: A
dynamic utility-maximizing model”, Journal of Business Venturing, Vol. 17 No. 3, pp. 189–
210.
Levie, J., Hart, M. and Anyadike-Danes, M. (2009), "The effect of Business or Enterprise
Training on Opportunity recognition and Entrepreneurial Skills of Graduates and non-
graduates in the UK,” Frontiers of Entrepreneurship Research, Vol. 29 No. 23, Article 1.
Available at: http://digitalknowledge.babson.edu/fer/vol29/iss23/1.
Levie, J., Hart, M. and Karim, M. S. (2010), Impact of Media on Entrepreneurial Intentions
and Actions, Global Entrepreneurship Monitor, November. Available at:
http://www.bis.gov.uk/assets/BISCore/enterprise/docs/I/11-773-impact-of-media-
entrepreneurial-intentions-actions.pdf.
Levy, M., Powell, P. and Worrall, L. (2005), “Strategic intent and E-Business in SMEs:
enablers and inhibitors”, Information Resources Management Journal, Vol. 18 No. 4, pp. 1-
20.
Linan, F., Urbano, D. and Guerrero, M. (2011), “Regional variations in entrepreneurial
cognitions: Start-up intentions of university students in Spain”, Entrepreneurship & Regional
Development, Vol. 23 Nos. 3-4, pp. 187-215.
Matlay, H. (2006), “Researching entrepreneurship and education Part 2: what is
entrepreneurship education and does it matter?”, Education + Training, Vol. 43 No. 8/9, pp.
395-404.
McLarty, R. (2005), “Entrepreneurship among graduates: towards a measured response”,
Journal of Management Development, Vol. 24 No. 3, pp. 223-238.
McClelland, D. C. (1961), The Achieving Society, Van Nostrand, Princeton, NY.
McClelland, D. C. and Winter, D. G. (1969), Motivating Economic Achievement, Free Press,
NY.
McMullen, J., Bagby, D. and Palich, L. (2008) “Economic Freedom and the Motivation to
Engage in Entrepreneurial Action”, Entrepreneurship Theory and Practice, Vol. 32 No. 5, pp.
875-895.
Miner, J. (1993), Role Motivation Theories, Routledge, New York.
Mingers, J. (2001), “Combining IS Research Methods: Towards a Pluralist Methodology”,
Information Systems Research, Vol. 12 No. 3, pp. 240-259.
Minniti, M., Arenius, P., and Langowitz, N. (2005), Global entrepreneurship monitor: 2004
report on women and entrepreneurship, Babson College and London Business School,
Babson Park, MA and London.
40
Muir, E., Atkinson, C. and Angrove, M. (2001), Welsh Entrepreneuses on the Web –
Executive Report, Welsh Enterprise Institute, University of Glamorgan.
Nyaribo, M., Prakash, A., and Edward, O. (2012), “Motivators of choosing a management
course: A comparative study of Kenya and India”, International Journal of Management
Education, Vol. 10, pp. 201-214.
Organisation for Economic Co-operation and Development (OECD) (2002), Management
Training in SMEs, Available at:
http://www.oecd.org/industry/smesandentrepreneurship/2492440.pdf.
Osborne, S. W., Falcone, T. W. and Nagendra, P. B. (2000), “From unemployment to
entrepreneur: a case study in intervention”, Journal of Development Entrepreneurship, Vol. 5
No. 2, pp. 115-136.
Packham, G., Jones, P., Miller, C., Pickernell, D. and Thomas, B. (2010), “Attitudes towards
entrepreneurship education: a comparative analysis”, Education + Training, Vol. 52 No. 8/9
pp 568-586.
Peterman, N. and Kennedy, J. (2003), “Enterprise education: influencing students’
perceptions of entrepreneurship”, Entrepreneurship Theory and Practice, Vol. 28 No. 2, pp.
129-44.
Peterson, R. and Limbu, Y. (2010), “Student characteristics and Perspectives in
Entrepreneurship courses: a profile”, Journal of Entrepreneurship Education, Vol. 13, pp. 66-
83.
Petridou, E., Sarri, A. and Kyrgidou, L. (2009), “Entrepreneurship education in higher
educational institutions: the gender dimension”, “Gender in Management: an International
Journal”, Vol. 24 No. 4, pp. 286-309.
Pickernell, D, Packham, G., Jones, P. Miller, C. and Thomas B. (2011), “Graduate
entrepreneurs are different: they have more knowledge?”, International Journal of
Entrepreneurial Behaviour and Research, Vol. 17 No. 2, pp. 183-202.
Pittaway, L. and Cope, J. (2007), “Entrepreneurship Education - A Systematic Review of the
Evidence”, International Small Business Journal, Vol. 25 No. 5, pp. 479-510.
Politis, D. (2005), “The process of Entrepreneurial Learning: A conceptual Framework”,
Entrepreneurial Theory and Practice, Vol. 29 No. 4, pp. 399-423.
Porter, L. W. and Lawler, E. E. (1968), Managerial attitudes and performance, Irwin-Dorsey
Homewood, Illinois.
Praag, C. and Versloot, P. (2007), “What is the value of entrepreneurship? A review of recent
research”, Small Business Economics, Vol. 29 No. 4, pp. 351-382.
Rae, D. (2007), “Connecting enterprise and graduate employability Challenges to the higher
education culture and curriculum?” Education + Training, Vol. 49 No. 8/9, pp. 605-619.
41
Reynolds, P., Bygrave, B. and Hay, M. (2003), Global Entrepreneurship Monitor Report, E.
M. Kauffmann Foundation, Kansas City.
Roberts, E. B. (1991), Entrepreneurs in High Technology, Oxford University Press, New
York.
Robinson, P. and Sexton E. (1994), “The effect of education and experience on self-
employment success”, Journal of Business Venturing, Vol. 9 No. 2, pp. 141-156.
Robson, P. and Bennett, R. (2000), “SME growth: the relationship with business advice and
external collaboration”, Small Business Economics, Vol. 15 No. 3, pp. 193-208.
Rosa, P. (2003), “Hardly likely to make the Japanese tremble: the businesses of recently
graduated university and college ‘entrepreneurs”, International Small Business Journal, Vol.
21 No. 4, pp. 435-459.
Russell, R., Atchison, M. and Brooks, R. (2008), “Business plan competitions in tertiary
institutions: encouraging entrepreneurship education”, Journal of Higher Education Policy
and Management, Vol. 30 No. 2, pp. 123-138.
Shane, S., Locke, E. A. and Collins, C. J. (2003), “Entrepreneurial motivation”, Human
Resource Management Review, Vol.13 No. 2, pp. 257–279.
Schwarz, E., Wdowiak, M., Almer-Jarz, D. and Breitenecker, R. (2009), “The effects of
attitudes and, perceived environment conditions on students’ entrepreneurial intent: An
Austrian perspective”, Education + Training, Vol. 51 No. 4, pp. 272-291.
Segal, G., Borgia, D. and Schoenfeld, J. (2005), “The motivation to become an entrepreneur”,
International Journal of Entrepreneurial Behaviour and Research, Vol. 11 No. 1, pp. 42-57.
Shafer, G. A. (1976), “Mathematical theory of Evidence”, Princeton University Press,
Princeton.
Solomon, G., Duffy, S. and Tarabishy, A. (2002), “The state of entrepreneurship education in
the United States: a nationwide survey and analysis”, International Journal of
Entrepreneurship Education, Vol. 1 No. 1, pp. 65-86.
Souitaris, V., Zerbinati, S. and Al-Laham, A. (2007), “Do entrepreneurship programmes raise
entrepreneurial intention of science and engineering students? The effect of learning,
inspiration and resources”, Journal of Business Venturing, Vol. 22, pp. 566–591.
Sprinthall, A. S., Sprinthall, R. C. and Oja, S. O. (1994), Educational Psychology. A
Developmental Approach, Addison-Wesley, Reading, MA.
Stewart, W., Watson, W. and Carland, J. (1999), “A proclivity for entrepreneurship: A
comparison of entrepreneurs, small business owners, and corporate managers”, Journal of
Business Venturing, Vol. 14 No. 2, pp. 189-214.
Storey, J., (2002), “A direct approach to false discovery rates”, Journal of the Royal
Statistical Society Series B, Vol 64 No 3, pp.479-498.
42
Taormina, R. and Lao, S. (2007), “Measuring Chinese entrepreneurial motivation:
Personality and environmental influences”, International Journal of Entrepreneurial
Behaviour and Research, Vol. 13 No. 4, pp. 200-221.
Tan, W. L., Tan, L. K., Tan, W. H. and Wong, S. C. (1995), “Entrepreneurial spirit amongst
tertiary students in Singapore”, Journal of Enterprise Culture, Vol. 3 No. 2, pp. 211-227.
Teichler, U. (2012), “Diversity of Higher Education in Europe and the Findings of a
Comparative Study of the Academic Profession”, European Higher Education at the
Crossroads, Part 7, pp. 935-959.
Van Stel, A. and Storey, D. (2004), “The Link between Firm Births and Job Creation: Is there
a up as Tree Effect?”, Regional Studies, Vol. 38 No. 8, pp. 893-909.
Von Graevenitz, G., Harhoff, D. and Weberb, R. (2010), “The effects of entrepreneurship
education”, Journal of Economic Behavior & Organization, Vol. 76 No. 3, pp. 90–112.
Walker, E., Redmond, J., Webster, B. and Le Cus, M. (2007), “Small business owners: too
busy to train?”, Journal of Small Business and Enterprise Development, Vol. 14, pp. 294-306.
Watson, K., Hogarth-Scott, S. and Wilson, N. (1998), “Small business start-ups: Success
factors and support implications”, International Journal of Entrepreneurial Behaviour and
Research, Vol. 4 No. 3, pp. 217-238.
Wennekers, S., Wennekers, A. V., Thurik, R. and Reynolds, P. (2005) “Nascent
Entrepreneurship and the Level of Economic Development”, Small Business Economics, Vol.
24 No. 3, pp. 293-309.
Wong, P. K., Ho, Y. P. and Autio, E. (2005), “Entrepreneurship, Innovation and Economic
Growth: Evidence from GEM data”, Small Business Economics, Vol. 24 No. 3, pp. 335-350.
Wu S., Matthews, L. and Dagher, G. K. (2007), “Need for achievement, business goals and
entrepreneurial persistence”, Management Research News, Vol. 30 No. 12, pp. 928–941.
Young, J. E. (1997), “Entrepreneurship education and learning for university students and
practising entrepreneurs”. In Sexton, D. L., Smilor, R.W. (Eds.), Entrepreneurship 2000.
Upstart Publishing Co, Chicago, Illinois, pp. 215-238.
Zeithaml, C. and Rice, G. (1987), “Entrepreneurship/small business education in American
Universities”, Journal of Small Business Management, Vol. 25 No. 1, pp. 44-50.
43
Figure 1: Visualisation of considered Motivation-Aspiration research problem
Figure 2: profiles the survey respondents by gender and age which reveals gender
representation in each age category.
44
Figure 3: Simplex plot based elucidation of relevance of motivations to segmentation of
self-employment (SE) and employment (E) aspirations of students
Figure 4: Direct relationship between response terms and mass values in motivation
BOEs
45
Figure 5: Simplex plot based elucidation of relevance of certain motivation
characteristics to discernment of self-employment (SE) and employment (E) aspirations,
with the added demographic of gender considered
Figure 6: Simplex plot based elucidation of relevance of certain motivation
characteristics to discernment of self-employment (SE) and employment (E) aspirations,
with the added demographic of age considered (1 - ‘18-24’, 2 - ‘25-34’, 3 - ‘35-44’, 4 -
‘45-54’ and 5 - ‘55-64’)
0
0.5
11
10
0
m xj,i({ })
m xj,i({¬ })
Ai
Bi
iv vj,i,1 vj,i,3
cf v( )i
01
0
m x xj,i({ , ¬ })
{ }x
pj,i,v
{¬ }x
{ , ¬ }x xa)
c)
b)
)(1
1ii vk
e
vj,i,2
m x1({ }) = 0.564
m x
m x x1
1
({¬ }) = 0.0
({ , ¬ }) = 0.436
m xC({ }) = 0.467
m x
m x xC
C
({¬ }) = 0.224
({ , ¬ }) = 0.309
m x2({ }) = 0.052
m x
m x x2
2
({¬ }) = 0.398
({ , ¬ }) = 0.550
46
Figure A1: Graphical representation of stages in CaRBS for a single characteristic
motivation value
Table 1: Likert scale employed within Research Instrument
1 2 3 4 5
Not
Important
Limited Contributory Important
Importance
Most
Important
Table 2: Student Enrolment by Gender 2002-06
Males
N1 = 337
Females
N2 = 383
Combined
NT = 720
Mean (M) 38.31 36.27 37.37
Median (Mdn) 37 35 36
Standard Dev. (SD) 11.22 10.52 10.94
top related